Data underlying the publication: Learning the mechanisms of network growth

This dataset accompanies the paper `Learning the mechanisms of network growth' by the same authors. The dataset contains 6733 networks of size 20,000 each generated in accordance to different combination of three mechanisms: fitness, aging and preferential attachment. The goal is to use machine learning to identify the combination of mechanisms that was used to create the network. The dataset includes static features from the literature and two version of our newly developed dynamic features. network growth

本数据集与同名作者发表的论文《网络生长机制学习》（Learning the mechanisms of network growth）配套发布。该数据集包含6733个节点规模均为20000的网络，所有网络均基于适应度（fitness）、老化（aging）与偏好依附（preferential attachment）三种机制的不同组合生成。本数据集的研究目标为借助机器学习方法，识别出用于构建对应网络的机制组合。数据集涵盖了源自现有文献的静态特征，以及两种全新开发的动态特征。